code: def dataset_strategy(draw):
      # Deifine strategies
      int_feature_strategy = st.integers(min_value=-10, max_value=10)
      float_feature_strategy = st.floats(min_value=-10, max_value=10)
      column_name_strategy = st.text(min_size=5, max_size=5)
      column_data_strategy = st.one_of(
          int_feature_strategy, float_feature_strategy
      )
  
      # Draw values
      col_names = draw(
          st.lists(
              column_name_strategy,
              min_size=NUM_COLS,
              max_size=NUM_COLS + 1,
              unique=True,
          )
      )
      label_name = draw(st.sampled_from(col_names))
      data = {
          name: draw(
              st.lists(column_data_strategy, min_size=5, max_size=5)
          )
          for name in col_names
      }
      dataset = Dataset.from_dict(data)
      dataset = dataset.rename_column(label_name, "label")
  
      # Make assertions about drawn values
      assume(len(set(dataset["label"])) > 1)
  
      return dataset
  
file_path: cleanlab/tests/datalab/test_data.py
imports: import tempfile
  from unittest.mock import patch
  import pytest
  from cleanlab.datalab.internal.data import Data, DataFormatError, DatasetLoadError
  from datasets import Dataset, ClassLabel
  import numpy
  import hypothesis.strategies
  from hypothesis import given, assume, settings, HealthCheck
label_desc: Use image node_id 1 for calling a global function with example usage: dataset_strategy(draw) and returns: dataset